189 lines
6.8 KiB
C++
189 lines
6.8 KiB
C++
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: mierle@gmail.com (Keir Mierle)
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//
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// An incomplete C API for Ceres.
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//
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// TODO(keir): Figure out why logging does not seem to work.
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#include "ceres/c_api.h"
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#include <vector>
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#include <iostream>
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#include <string>
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#include "ceres/cost_function.h"
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#include "ceres/loss_function.h"
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#include "ceres/problem.h"
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#include "ceres/solver.h"
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#include "ceres/types.h" // for std
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#include "glog/logging.h"
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using ceres::Problem;
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void ceres_init() {
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// This is not ideal, but it's not clear what to do if there is no gflags and
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// no access to command line arguments.
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char message[] = "<unknown>";
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google::InitGoogleLogging(message);
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}
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ceres_problem_t* ceres_create_problem() {
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return reinterpret_cast<ceres_problem_t*>(new Problem);
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}
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void ceres_free_problem(ceres_problem_t* problem) {
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delete reinterpret_cast<Problem*>(problem);
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}
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// This cost function wraps a C-level function pointer from the user, to bridge
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// between C and C++.
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class CallbackCostFunction : public ceres::CostFunction {
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public:
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CallbackCostFunction(ceres_cost_function_t cost_function,
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void* user_data,
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int num_residuals,
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int num_parameter_blocks,
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int* parameter_block_sizes)
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: cost_function_(cost_function),
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user_data_(user_data) {
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set_num_residuals(num_residuals);
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for (int i = 0; i < num_parameter_blocks; ++i) {
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mutable_parameter_block_sizes()->push_back(parameter_block_sizes[i]);
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}
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}
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virtual ~CallbackCostFunction() {}
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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return (*cost_function_)(user_data_,
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const_cast<double**>(parameters),
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residuals,
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jacobians);
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}
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private:
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ceres_cost_function_t cost_function_;
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void* user_data_;
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};
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// This loss function wraps a C-level function pointer from the user, to bridge
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// between C and C++.
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class CallbackLossFunction : public ceres::LossFunction {
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public:
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explicit CallbackLossFunction(ceres_loss_function_t loss_function,
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void* user_data)
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: loss_function_(loss_function), user_data_(user_data) {}
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virtual void Evaluate(double sq_norm, double* rho) const {
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(*loss_function_)(user_data_, sq_norm, rho);
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}
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private:
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ceres_loss_function_t loss_function_;
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void* user_data_;
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};
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// Wrappers for the stock loss functions.
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void* ceres_create_huber_loss_function_data(double a) {
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return new ceres::HuberLoss(a);
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}
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void* ceres_create_softl1_loss_function_data(double a) {
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return new ceres::SoftLOneLoss(a);
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}
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void* ceres_create_cauchy_loss_function_data(double a) {
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return new ceres::CauchyLoss(a);
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}
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void* ceres_create_arctan_loss_function_data(double a) {
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return new ceres::ArctanLoss(a);
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}
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void* ceres_create_tolerant_loss_function_data(double a, double b) {
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return new ceres::TolerantLoss(a, b);
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}
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void ceres_free_stock_loss_function_data(void* loss_function_data) {
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delete reinterpret_cast<ceres::LossFunction*>(loss_function_data);
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}
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void ceres_stock_loss_function(void* user_data,
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double squared_norm,
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double out[3]) {
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reinterpret_cast<ceres::LossFunction*>(user_data)
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->Evaluate(squared_norm, out);
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}
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ceres_residual_block_id_t* ceres_problem_add_residual_block(
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ceres_problem_t* problem,
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ceres_cost_function_t cost_function,
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void* cost_function_data,
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ceres_loss_function_t loss_function,
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void* loss_function_data,
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int num_residuals,
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int num_parameter_blocks,
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int* parameter_block_sizes,
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double** parameters) {
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Problem* ceres_problem = reinterpret_cast<Problem*>(problem);
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ceres::CostFunction* callback_cost_function =
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new CallbackCostFunction(cost_function,
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cost_function_data,
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num_residuals,
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num_parameter_blocks,
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parameter_block_sizes);
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ceres::LossFunction* callback_loss_function = NULL;
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if (loss_function != NULL) {
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callback_loss_function = new CallbackLossFunction(loss_function,
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loss_function_data);
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}
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std::vector<double*> parameter_blocks(parameters,
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parameters + num_parameter_blocks);
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return reinterpret_cast<ceres_residual_block_id_t*>(
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ceres_problem->AddResidualBlock(callback_cost_function,
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callback_loss_function,
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parameter_blocks));
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}
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void ceres_solve(ceres_problem_t* c_problem) {
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Problem* problem = reinterpret_cast<Problem*>(c_problem);
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// TODO(keir): Obviously, this way of setting options won't scale or last.
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// Instead, figure out a way to specify some of the options without
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// duplicating everything.
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ceres::Solver::Options options;
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options.max_num_iterations = 100;
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options.linear_solver_type = ceres::DENSE_QR;
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options.minimizer_progress_to_stdout = true;
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ceres::Solver::Summary summary;
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ceres::Solve(options, problem, &summary);
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std::cout << summary.FullReport() << "\n";
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}
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